code: def test_extract_patterns_use_only_entities_regexes(
      entity: Text,
      regex_features: Dict[Text, Text],
      expected_patterns: Dict[Text, Text],
  ):
      training_data = TrainingData()
      if entity:
          training_data.training_examples = [
              Message(
                  data={
                      "text": "text",
                      "intent": "greet",
                      "entities": [{"entity": entity, "value": "text"}],
                  }
              )
          ]
      if regex_features:
          training_data.regex_features = [regex_features]
  
      actual_patterns = pattern_utils.extract_patterns(
          training_data, use_only_entities=True
      )
  
      assert actual_patterns == expected_patterns
  
file_path: rasa/tests/nlu/utils/test_pattern_utils.py
imports: from typing import Dict, List, Text
  import pytest
  import rasa.nlu.utils.pattern_utils
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 2 for calling a global function with example usage: test_extract_patterns_use_only_entities_regexes(entity, regex_features, expected_patterns) without return types